Prescribing of lipid regulating drugs and admissions for myocardial infarction in England
BMJ 2004; 329 doi: https://doi.org/10.1136/bmj.329.7467.645 (Published 16 September 2004) Cite this as: BMJ 2004;329:645Data supplement
Dr Foster’s case notes
Prescribing of lipid-regulating drugs and admissions for myocardial infarction in England
[posted as supplied by author]
References
w1 Department of Health. National service framework for coronary heart disease. London: HMSO, 2000.
w2 Scandinavian Simvastatin Survival Study Group. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet 1994;344:1383-9.
w3 Shepherd J, Cobbe SM, Ford I, Isles CG, Lorimer AR, Macfarlane PW, et al. Prevention of coronary heart disease in men with hypercholesterolaemia. N Engl J Med 1995;333:1301-7.
w4 Collins R, Armitage J, Parish S, Sleight P, Peto R. Heart Protection Study Collaborative Group. Effects of cholesterol-lowering with simvastatin on stroke and other major vascular events in 20536 people with cerebrovascular disease or other high-risk conditions. Lancet 2004;363:757-67.
w5 Majeed A, Evans N, Head P. What can PACT tell us about prescribing in general practice? BMJ 1997;315:1515-9.
w6 Mckenna CJ, Forfar JC. Was it a heart attack? BMJ 2002;324:377–8.
Methodology
In this month’s Dr Foster’s case notes our statistics do not include prescriptions issued and dispensed in hospitals, but most prescriptions for lipid regulating agents are likely to be issued by general practitioners. The admissions data will exclude patients treated at home or admitted to private hospitals, but these are likely to account for a small proportion of all patients diagnosed with a myocardial infarction (some cases will be undiagnosed and will therefore be missed entirely). Our data also excluded patients who died before they got to hospital.
The Dr Foster case note is based on analysis of Hospital Episode Statistics (HES) and NHS prescribing data. HES data is routinely collected within the health service for administrative purposes and not specifically for clinical audit. There may be issues around coverage, completeness and accuracy that need to be considered when interpreting the results. In addition, the capacity to adjust for confounding factors is in general limited to the information available in the data, although where appropriate, we are able to adjust by socio-economic deprivation using the postcode of residence.
HES data are submitted by all NHS hospital trusts in England and capture all admissions, both inpatients and day cases, and also include deaths occurring in hospital, recording details such as the patient’s age and diagnosis and any operations they had. The data are in the form of consultant episodes (the continuous period during which the patient is under the care of one consultant), which need to be linked into "spells" or admissions for some analyses. About 10% of spells comprise more than one episode, and the patient’s method and date of discharge need to be derived from the final episode in the spell.
Data fields can contain missing or invalid values and spells may be incomplete. Episodes are assumed to be duplicates if they have the same combination of provider, date of birth, sex, postcode, date of admission and episode number (PROCODE, DOB, SEX, HOMEADD, EPISTART, EPIEND, EPIORDER). Duplicates are excluded at this stage.
Some spells have the same date of admission (ADMIDATE) but different dates of discharge (DISDATE). This is not valid unless the patient was discharged and readmitted on the same day, and the spell with the earliest ADMIDATE was arbitrarily taken to be the valid one. Episodes relating to the invalid spell are excluded at this stage.
Where analyses require episodes linked together to form spells, for years before 2000/1, records are assumed to belong to the same person if they match on date of birth, sex and postcode (DOB, SEX, HOMEADD) as the NHS number is not complete or accurate enough. Episodes with invalid DOB (recorded by HES as 15th Oct 1582) or SEX (i.e. not ‘1’ or ‘2’) are excluded at this stage. From 2000/1 we have been given HESID, derived by the Department of Health, and have been using this as a patient identifier. Only ages within the ranges 1-120 and 7001-7007 (special values to indicate age in months for children under 1 year) are considered valid.
Also excluded at this stage are unfinished episodes (EPISTAT=1), unknown/invalid method of admission (ADMIMETH <> 11,12,13,21,22,23,24,28,81). Episode linkage is not of course performed on day cases, which are discarded for projects involving only inpatients.
Remaining episodes are sorted by provider, date of birth, sex, postcode, date of admission, date of discharge and episode number (PROCODE, DOB, SEX, HOMEADD, ADMIDATE, DISDATE, EPIORDER). Episodes are not required to be in strict sequence, only in chronological order. For example, if the first one had EPIORDER=01, the second one had EPIORDER=03 and the last one of the same spell had EPIORDER=99, then the three episodes are treated just the same as if they were numbered 01, 02 and 03 (as most multi-episode spells are). The dataset is then split into the first and last episodes of each spell (which are often the same, as most spells comprise only one episode). Diagnosis and procedure variables are taken from the first episode (DIAG1-DIAG7, OPER1-OPER4, date of primary procedure OP_DTE_1). Outcome variables are taken from the last episode (DISMETH (method of discharge), DISDEST (destination on discharge), DISDATE). DISMETH=’4’ is used to indicate death (it does not always coincide with DISDEST=’79’ but it is used by the DH).
Mention of ICD10 codes I21 (Acute MI) and I22 (Subsequent MI) in the primary diagnosis in the first episode of each spell was used to select spells for this analysis. Standardised admission ratios were adjusted by age and sex and ONS mid year population estimates for all England. The PCT area based comparisons use ONS 2001 census populations.
The national prescribing data came from the Department of Health’s Prescription Cost Analysis system, which collates information on all prescriptions dispensed in the community. The data on prescribing for primary care trusts came from the PACT system, which collates information on prescriptions issued by general practitioners.
The Prescription Prescribing Authority collects information on all prescriptions issued by general practitioners that are dispensed by community pharmacists, dispensing general practitioners, or appliance contractors. The information collected includes the name and cost of the drug and the number of items dispensed (an item is defined as each preparation on the prescription). The drugs dispensed are then used to calculate the cost of each item. Drugs are categorised by the section of the British National Formulary that they fall in. Hence, information is available for individual drugs (such as simvastatin), for categories of drugs (such as lipid-regulating drugs), or for therapeutic areas (such as cardiovascular drugs). This information is available at general practice, primary care trust, and national levels.
Our statistics do not include prescriptions issued and dispensed in hospitals, but most prescriptions for lipid regulating agents are likely to be issued by general practitioners. The admissions data will exclude patients treated at home or admitted to private hospitals, but these are likely to account for a small proportion of all patients diagnosed with a myocardial infarction (some cases will be undiagnosed and will therefore be missed entirely). Our data also excluded patients who died before they got to hospital.
Although PACT data have many uses and are often used for research and NHS management, they do have some important limitations. The most important is that the data provide only a narrow range of information, mainly on what drugs were prescribed and how much the prescribed drugs cost. Secondly, the data cannot be linked routinely to demographic or clinical data on patients. Hence, they cannot be used to calculate age and sex specific prescribing rates or to look at prescribing rates for specific conditions. Thirdly, because they are based on dispensed NHS prescriptions, they do not include private prescriptions or prescriptions that a patient does not have dispensed. Fourthly, the number of items prescribed is not always an accurate measure of the amount of a drug actually prescribed. Defined daily doses (which can be calculated from PACT data) can be used to overcome this problem and provide a more accurate measure of the amount of a drug prescribed than the number of items. Finally, PACT tells us only about the prescribing carried out in general practice and does not contain any information on prescribing in hospitals.
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